dc.contributor.authorSahoo, Sujit Kumar
dc.contributor.authorAnamitra Makur (EEE)
dc.identifier.citationSujit, K. S., & Anamitra Makur. (2015). Enhancing image denoising by controlling noise incursion in learned dictionaries. IEEE signal processing letters, 22(8), 1123-1126.en_US
dc.description.abstractExisting image denoising frameworks via sparse representation using learned dictionaries have an weakness that the dictionary, trained from noisy image, suffers from noise incursion. This paper analyzes this noise incursion, explicitly derives the noise component in the dictionary update step, and provides a simple remedy for a desired signal to noise ratio. The remedy is shown to perform better both in objective and subjective measures for lesser computation, and complements the framework of image denoising.en_US
dc.format.extent4 p.en_US
dc.relation.ispartofseriesIEEE signal processing lettersen_US
dc.rights© 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: [http://dx.doi.org/10.1109/LSP.2015.2388712].en_US
dc.subjectDRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing
dc.titleEnhancing image denoising by controlling noise incursion in learned dictionariesen_US
dc.typeJournal Article
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.versionAccepted versionen_US

Files in this item


This item appears in the following Collection(s)

Show simple item record